AI RESEARCH
JSON-Bag: A generic game trajectory representation
arXiv CS.LG
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ArXi:2508.00712v2 Announce Type: replace Our approach outperforms a baseline using hand-crafted features in the majority of tasks. Evaluating on N-shot classification suggests using JSON-Bag prototype to represent game trajectory classes is also sample efficient. Additionally, we nstrate JSON-Bag ability for automatic feature extraction by treating tokens as individual features to be used in Random Forest to solve the tasks above, which significantly improves accuracy on underperforming tasks.